Are Participants in Pharmacological and Psychotherapy Treatment Trials for Social Anxiety Disorder Representative of Patients in Real-Life Settings?
Bibliographic record
Abstract
BACKGROUND: The present study sought to quantify the generalizability of clinical trial results in individuals with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, diagnosis of social anxiety disorder (SAD) to a large representative community sample. METHODS: Data were derived from the 2004-2005 National Epidemiologic Survey on Alcohol and Related Conditions, a large nationally representative sample of 34,653 adults from the US population. We applied a standard set of exclusion criteria representative of pharmacological and psychotherapy clinical trials to all adults with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, diagnosis of SAD (n = 965) in the past 12 months and then to a subsample of participants seeking treatment (n = 363). Our aim was to assess how many participants with SAD would fulfill typical eligibility criteria. RESULTS: We found that more than 7 of 10 respondents from the overall SAD sample in a typical pharmacological efficacy trial and more than 6 of 10 participants in a typical psychotherapy efficacy trial would have been excluded by at least 1 criterion. In addition, more than 8 of 10 respondents seeking treatment for SAD would have been excluded from participation in a typical pharmacological or psychotherapy efficacy trial. Having a current major depression explained a large proportion of ineligibility. CONCLUSIONS: Clinical trials should carefully consider the impact of exclusion criteria on the generalizability of their results and explain the rationale for their use. For SAD treatment trials to adequately inform clinical practice, the eligibility rate must be increased through a general relaxation of overly stringent eligibility criteria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.403 | 0.679 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".